PartCensReg: Estimation and Diagnostics for Partially Linear Censored Regression Models Based on Heavy-Tailed Distributions

It estimates the parameters of a partially linear regression censored model via maximum penalized likelihood through of ECME algorithm. The model belong to the semiparametric class, that including a parametric and nonparametric component. The error term considered belongs to the scale-mixture of normal (SMN) distribution, that includes well-known heavy tails distributions as the Student-t distribution, among others. To examine the performance of the fitted model, case-deletion and local influence techniques are provided to show its robust aspect against outlying and influential observations. This work is based in Ferreira, C. S., & Paula, G. A. (2017) <doi:10.1080/02664763.2016.1267124> but considering the SMN family.

Version:	1.39
Imports:	ssym, optimx, Matrix
Suggests:	SMNCensReg, AER
Published:	2018-03-08
DOI:	10.32614/CRAN.package.PartCensReg
Author:	Marcela Nunez Lemus, Christian E. Galarza, Larissa Avila Matos, Victor H Lachos
Maintainer:	Marcela Nunez Lemus <marcela.nunez.lemus at gmail.com>
License:	GPL-2 | GPL-3 [expanded from: GPL (≥ 2)]
NeedsCompilation:	no
CRAN checks:	PartCensReg results

Documentation:

Reference manual:

PartCensReg.pdf

Downloads:

Package source:	PartCensReg_1.39.tar.gz
Windows binaries:	r-devel: PartCensReg_1.39.zip, r-release: PartCensReg_1.39.zip, r-oldrel: PartCensReg_1.39.zip
macOS binaries:	r-release (arm64): PartCensReg_1.39.tgz, r-oldrel (arm64): PartCensReg_1.39.tgz, r-release (x86_64): PartCensReg_1.39.tgz, r-oldrel (x86_64): PartCensReg_1.39.tgz
Old sources:	PartCensReg archive

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